Data Scientist

Meta · Big Tech · Menlo Park, CA

Data Scientist role at Meta focused on collecting, organizing, interpreting, and summarizing statistical data to contribute to product design and development. The role involves quantitative analysis, data mining, and data presentation to understand user interactions with consumer and business products. It requires partnership with Product and Engineering teams to solve problems, identify trends, and influence product decisions. Responsibilities may include product operations, exploratory analysis, product influence, and data infrastructure projects, working on problems of moderate scope where analysis of situations or data requires a review of a variety of factors. Requires a Bachelor's degree in a quantitative field and experience in quantitative analysis, data querying (SQL), scripting (Python), statistical software (R, SAS, or Matlab), applied statistics/experimentation (A/B testing), Machine Learning techniques, ETL, and relational databases.

What you'd actually do

Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of Facebook products.
Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products.
Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
Inform, influence, support, and execute our product decisions and product launches.
May be assigned projects in various areas including, but not limited to, product operations, exploratory analysis, product influence, and data infrastructure.

Skills

Required

Bachelor's degree in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or a related field
Performing quantitative analysis including data mining on highly complex data sets
Data querying language(s) including SQL
Scripting language(s) including Python
Statistical or mathematical software including one of the following: R, SAS, or Matlab
Applied statistics or experimentation, such as A/B testing, in an industry setting
Machine Learning techniques
ETL (Extract, Transform, Load) processes
Relational databases

Read full job description

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.

Responsibilities

Collect, organize, interpret, and summarize statistical data in order to contribute to the design and development of Facebook products. Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products. Partner with Product and Engineering teams to solve problems and identify trends and opportunities. Inform, influence, support, and execute our product decisions and product launches. May be assigned projects in various areas including, but not limited to, product operations, exploratory analysis, product influence, and data infrastructure. Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors. Exercise judgment within defined procedures and practices to determine appropriate action.

Qualifications

Requires Bachelor's degree( Foreign degree equivalent accepted)in Statistics, Mathematics, Data Analytics, Computer Science, Engineering, Information Systems, Applied Sciences, or a related field and Completion of an undergraduate-level course, research project, or internship involving the following: Performing quantitative analysis including data mining on highly complex data sets Data querying language(s) including SQL Scripting language(s) including Python Statistical or mathematical software including one of the following: R, SAS, or Matlab Applied statistics or experimentation, such as A/B testing, in an industry setting Machine Learning techniques ETL (Extract, Transform, Load) processes and Relational databases